How to use no-code AI for NPS and Customer Tickets

How to use no-code AI for NPS and Customer Tickets

Hanna Kleinings

Success Builder

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Keeping customers happy is one of the keys to a successful business. The customer is king, after all.

However, doing so consistently can be difficult, and it requires you keep a good watch over what your customers think of your product. One way to do this is with a net promoter score (NPS).

Many businesses use the net promoter score as one of their key performance indicators—there’s a reason that two-thirds of Fortune 1000 companies use this metric. It's easy to track, and the results can be used to predict other measures like client retention and profitability.

The key, of course, lies in how you use the results of your NPS survey analysis to improve your overall business performance. In this article, we’re talking about the importance of NPS, why you should analyze survey text, and how to streamline and automate the entire process.

Let’s jump in!

What is the net promoter score (NPS)?

The net promoter score (NPS) is a metric used in customer experience programmes for assessing customer loyalty. Many businesses use it to evaluate client satisfaction, forecast business development, and growth.

The concept of NPS has been around since 2003. According to bestselling business author Frederick F. Reichheld—there’s not more than one key question you need to ask:

“How likely is it that you would recommend [company X] to a friend or colleague?”

The response is a strong indicator of a company's overall development and achievement.

Respondents are divided into three categories based on their responses on a 0–10 scale:

  • Promoters (9–10) are loyal consumers who will continue to buy from you and recommend you to others. Promoters assist company growth.
  • Passives (7–8) are mainly content but unconcerned. Your competitors can easily win their attention.
  • Detractors (0–6) are dissatisfied consumers. They could harm progress by spreading bad reviews, and are likely to churn.
Table showing characteristics of the different respondent categories of the NPS
Different categories for respondents on the NPS

Calculating your final NPS score is very simple. You’ll need to subtract the percentage of Detractors from the percentage of Promoters. This is what it should look like:

NPS Score = %Promoters — %Detractors

Let’s say that 40% of respondents are Promoters and 35% are Detractors. The calculation would go as follows:

40% — 35% = 5%

According to Bain & Company, the creators of NPS, this is the benchmark for your NPS results. You want to calculate your NPS score and compare it to these figures:

  • Above 0% is good,
  • Above 20% is favorable
  • Above 50% is excellent
  • Above 80% is world-class

The subsequent sections of the survey should then ask consumers to elaborate on their ratings in more detail. This way, you’ll be able to get deeper insights into what drives your customers to like or dislike your services. This is the qualitative part of the research which you also need to take into consideration to identify the areas of your business that need improvement.

Why is NPS important?

Data-driven business decisions can help you maximise the results you’ll get from your growth strategy, and the NPS score is no exception.  Net Promoter leaders outgrow their competition by 2.5 times in most sectors, and a 12-point boost in Net Promoter Scores results in a company's growth rate tripling on average. Prioritizing your NPS gets tangible results for your business.

Some reasons why you need to measure NPS to improve your business performance are:

  • It’s simple to measure: There are no complicated formulas. Moreover, you can easily understand what it means. NPS makes customer loyalty a measurable term with minimal hassle.
  • It encompasses all user feelings about your company: It’s not based only on one purchase. As a result, NPS is applicable to all while also being simply digested as a single figure—it’s a broader view.
  • It helps you determine your market position: Compare your NPS to your industry benchmark to find out where you stand in the market.
  • It can serve as a growth prediction: NPS shows the likelihood of consumers to return, allowing you to estimate your brand's prospective growth, profitability, and condition.
  • Open-ended questions can provide valuable information: The qualitative data from client responses can help you determine your messaging, identify potential improvement spots, and create a product that satisfies customer needs.

The challenge with NPS

NPS is pretty simple to calculate. However, it’s not that easy to leverage. Many companies find this out the hard way.

For example, if you have surveyed 100 customers, with 40% being Promoters, 25% being Detractors, and 35% being Passives, some more questions come up.

  • Why do the Detractors have a negative opinion about your brand?
  • How can you improve their experience?
  • How can the Passives become Promoters?
  • Is there something Promoters would like to improve?

You can’t answer all these questions with just a quantitative response.

For example, if a Detractor has had a negative encounter with your business, you’ll want to know what that is.

That’s why it’s essential to collect qualitative answers. The process doesn’t end after asking one question, it is essential to have a follow-up plan.

One single question will hardly be eye-opening. You’ll need to create a set of specific questions that can pinpoint the anomalies of your business. With open-ended questions, you can get input on a variety of issues as well as the NPS numbers you need.

Your NPS survey should send customers down a unique route depending on their initial answers. For example, if they are unhappy with your service, the survey should automatically send them to specific questions. This not only improves the quality of insights, but also shows the participant that you are paying attention to their remarks.

This brings us to the real challenge: examining the open-ended answers you collect. This process can be quite difficult and time-consuming—if you’re not using Artificial Intelligence (AI) to perform NPS sentiment analysis, that is.

Don’t worry, you won’t have to code anything. You can use no-code AI to gather and analyze your wordy replies alongside your data. You can subsequently employ sophisticated conversational surveys to get to the bottom of any problems.

How to make your customer feedback actionable?

Scanning through page after page of survey responses is time-consuming and inefficient. A no-code, AI-based analysis can take care of the legwork for you, sifting through the replies to uncover the trends and information you want.

Thanks to NLP and Sentiment Analysis, you can rapidly see which aspects of your service aren’t meeting your client's expectations by analyzing frequent themes and attitudes. This enables you to identify the stories behind your NPS survey replies and provide greater insights through comprehensive NPS sentiment analysis and customer cohorts.

Let’s see how you can turn feedback into action with no-code machine learning.

Classify open-ended feedback

Going through open-ended replies and categorizing them into predetermined subjects is the first step to your NPS sentiment analysis. For example, you could tag them according to the feature/service they refer to, like:

  • Customer support
  • Usability
  • Performance
  • Automation feature

These are just some examples—you need to consider what it is you’re looking to find.

An example of  a Levity flow classifying customer insights
Levity flow classifying customer insights

You might also assign a sentiment to each open-ended response, which can then push you to take action in a variety of ways:

Positive feedback

This feedback can help you identify product champions. NPS and follow-up questions can assist in determining the most critical business areas to focus on. They’ll likely be using words like ‘love’ or ‘enjoy’ to express their satisfaction.

By using methods like NPS sentiment analysis, you can figure out which aspects of the customer experience have the most emotional impact or which have the strongest association with total NPS. You can give a better experience faster by prioritizing these elements.

The products and features people highlight in their positive feedback enable you to effectively prioritize the promotion and development of a specific feature. Let’s see this example:

“I love how organized your tool makes me. I especially like the possibility to time-track all my tasks. It saves a lot of valuable time.”

This means that you could increase advertising focus on your time-track feature or expand it further to make it even better. You could also consider introducing an in-app tooltip to highlight this feature for users that are currently missing it—helping build your retention rates.

Make sure you thank positive reviewers for their kind words, and for taking the time to complete your survey.

Negative feedback

Here’s where you’re likely to get responses that highlight ‘dislikes’ and ‘difficulties’. These are the customers that have issues with your product or service.

Those who respond negatively are prone to venting their distaste on social media or SaaS review sites like Capterra and G2—not what you want. For example, if a person says that they’ve had constant problems with one of your features, a single tweet can quickly snowball.

You can handle this by offering them an opportunity to talk it through with a real person. This way, you'll not only halt the negative publicity, but you'll also give yourself a chance to learn from your customer’s experience, and perspective while enabling your team to fix the problem and transform your client's perception of your business.

Neutral feedback

This is a little trickier to pinpoint, but you’re likely looking out for the ‘standard’ and ‘ok’ reviews. They don’t love you, but they don’t hate you—they’re indifferent.

Neutral reviews can be used to identify areas to promote features, promotions, or other exciting news that would be improper to disclose to negative reviewers. Additional perks or rewards can turn a neutral reviewer into a promoter and improve your NPS score.

Make sure you thank them for the positive side of the review but also acknowledge the negative side. Apologize for the inconvenience and provide them assistance from a real person to improve your brand image, and product, in their eyes.

Classification enables you to evaluate the outcomes of open-ended replies and put your NPS ratings into perspective.

Note: Levity allows you to classify textual customer feedback such as internet reviews, interview transcripts, and emails in real-time. Sort by topic, sentiment, or whichever criteria are most important to you. This can save a lot of time and help you identify the answers that really require you to dive in.

Define and identify trends

It's critical to keep track of survey response findings to look for trends over time.

For example, if several customers complain about the customer service process, it may be time to revise and improve it.

Or, if there’s a bug causing issues for a certain feature, you could address it by hiring a developer specialized in that feature. After solving the issue, you could send out another survey and compare the two NPS scores to find out if this action improved customer satisfaction.

This methodical approach to customer feedback can assist you in detecting sentiment and determining if customers like your new feature. Moreover, you can validate new hypotheses or see if your customer service process really answers customer needs. Sometimes they require additional tutorials or a simpler user experience. Or, it could also be that your pricing doesn't fit the target’s budget.

Put simply, assessing client feedback over time allows you to see what it is that you're doing right, and what you’re doing wrong. This helps you consistently deliver customer-centric products, as well as attract and retain more customers.

How to optimize customer ticket processes with AI

In addition to your NPS survey analysis, you can also optimize customer ticket processes with no-code AI. This helps:

  • Ensure a high standard of client satisfaction.
  • Maintain a low cost of operation while you deal with increased ticket demand.
  • Assist with the business's overall planning and expansion.

Depending on the responses to your NPS, this could be a game-changer.

Note: Levity's software assigns tags automatically based on the subject and content of the request. For sentiment analysis, urgency, and language identification, choose from one of our pre-built models. Create your own custom model to detect products, divisions, and other factors unique to your company.

Identify actionable insights by topic

Topic analysis is a method of interpreting and categorizing enormous amounts of info into specific subjects or topics.

Let’s take this feedback, for example:

“The customer support team was helpful but the process was a bit time-consuming. I think the problem could have been solved faster.”

A pre-trained model could identify “customer support” and “time-consuming.” These keywords could be classified under the topics of Customer Support and Performance. In this case, the customer support team could reach out and identify the process that took longer than expected and try to optimize it.

Find the right person for urgency

To solve problems faster, you should notify the right professional or team who can get to the root cause. If we take the previous example, it’s essential that you notify the customer support team so they can react in real-time.

Another example could be that a person is complaining that a certain feature is slower than the rest. This feedback should inform the product or development team that the highlighted feature needs improving. This way, the problem can be fixed efficiently, and teams can report back to customers to let them know it’s resolved.

Note: Levity enables you to automatically notify the relevant team or person via Slack, Gmail, and a wide variety of other integrations.

Develop customer-centric next steps

One of the most important benefits of employing AI customer tickets is that you can develop your own model and customize labels according to your needs. You can define your own decision tree.

Decision Tree
Decision Tree

The decision tree represents your decision-making process. In AI, decision trees form opinions based on the evidence available from previous judgments. These findings are given numerical values, which are then used to inform key decisions.

To put it simply, you can categorize and view data in a way that aligns with what matters most to your users.

You set up your own rules for the AI model, which become the basis of the decisions it makes. You can add the emotions that matter and the categories you can use to further improve your products and make them customer-centric.

Once you’ve gathered your customer feedback and developed a plan of action, you need a quick and easy way to manage and track progress—you need a ticketing system.

Best ticketing systems for customer feedback management

Here are some of the best ticketing systems you could consider:

  • Zendesk: if you want a marketing-focused ticket system.
  • Microsoft Ticketing System: for large enterprises and experienced staff.
  • Helpdesk: best for startups, freelancers, and personal use.
  • Freshdesk: for an easy-to-use automation with a variety of marketing and sales tools.
  • Kayako: a budget-friendly option for easier communication with clients.
  • Zoho Desk: with affordable rates and a number of integrations.

You can use all of these ticketing systems with Levity.

You can share NPS data between multiple applications with a strong API and built-in compatibility for many popular apps. Thanks to integrations with Zapier, Zendesk, Intercom, Google Sheets, and more, you can easily transfer NPS data for simple analysis.

Wrapping up on no-code AI for NPS and customer tickets

No-code AI is transforming the way companies examine NPS data and handle customer ticket outcomes. Automation is the way forward—it’s efficient and reliable.

Consider the task of sorting through countless NPS answers and customer tickets. You could sift through this data by hand, but the findings would most certainly be susceptible to bias and human error. Plus, your time is better spent on other areas of business development.

Now, imagine teaching machine learning models to recognize the sentiments, topics, and urgency behind your NPS text analysis. Getting valuable information sounds a lot simpler, right?

Levity provides a number of features that can classify the results of your NPS survey analysis and customer tickets and save you time. Join a demo today to learn how Levity can help you to start rising above mundane tasks and start automating key business processes.

Now that you're here

Levity is a tool that allows you to train AI models on images, documents, and text data. You can rebuild manual workflows and connect everything to your existing systems without writing a single line of code.

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